Dietary intake of low-income adults in South Africa: ultra-processed food consumption a cause for concern
Bibliographic record
Abstract
OBJECTIVE: Given the rapidly changing food environment and proliferation of ultra-processed foods (UPF) in South Africa (SA), this study aimed to critically evaluate dietary quality and adequacy of low-income adults using the Nova classification system and WHO and World Cancer Research Fund dietary guidelines. DESIGN: Secondary household data and 1-d 24-h recalls were analysed from two cross-sectional studies conducted in 2017-2018. Foods consumed were classified according to the Nova classification system. Compliance with WHO dietary guidelines and UPF consumption trends were evaluated. SETTING: Three low-income areas (Langa, Khayalitsha and Mount Frere) in SA were included. PARTICIPANTS: In total, 2521 participants (18-50 years) were included in the study. RESULTS: Participants had a mean energy intake of 7762 kJ/d. Most participants were within the acceptable WHO guideline range for saturated fat (80·4 %), total fat (68·1 %), Na (72·7 %) and free sugar (57·3 %). UPF comprised 39·4 % of diets among the average adult participant. Only 7·0 % of all participants met the WHO guideline for fruit and vegetables and 18·8 % met the guideline for fibre. Those within the highest quartile of share of energy from UPF consumed statistically higher amounts of dietary components to limit and were the highest energy consumers overall. CONCLUSIONS: Low-income adults living in SA are consuming insufficient protective dietary components, while UPF consumption is prevalent. Higher UPF consumers consume larger amounts of nutrients linked to increased chronic disease risk. Policy measures are urgently needed in SA to protect against the proliferation of harmful UPF and to promote and enable consumption of whole and less UPF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".